Extrusion: Self-Diagnostic Software For Extruders

Problem alerts personnel to heater solenoid failure, feeding issues, gearbox vibration, and general equipment failures.

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Apex Machine, Calvert City, Ky., has developed a self-diagnostic extruder program that it says can detect equipment and process anomalies based on data streaming from the machine. Machine data is captured live and forwarded to the Apama streaming statistical-analysis program from Software AG in Germany (softwareag.com). 

The program is “trained” to detect patterns and trigger an action when one of the learned anomalies is detected. Examples of possible anomalies are heater solenoid failure, feeding issues, gearbox vibration, and general equipment failures.

When an anomaly is detected, the program highlights the general area of the machine and turns yellow on the data-streaming panel. It also gives an instruction if it’s a detailed fault such as a stuck heater solenoid or feeding issue. Setup does not require the machine to be connected to the cloud; it’s all done at the machine on a Dell Edge Gateway device.

Additional data can be stored in the cloud as an option, however. The system can be set up to “talk to” maintenance and MES systems. This allows for maintenance and production alerts to go out automatically with little or no human interaction at the machine.