The Woodruff School

SUMMARY

The usage of external sensors for machine health monitoring is becoming more popular. A variety of methods for monitoring the condition of CNC machines have been developed by researchers. This study focuses on automation principles for these methods connecting an edge device for sensor data acquisition to the OPC UA controller server of a CNC machine. For this purpose, two different architectures are developed and analyzed in experiments to identify the limitations regarding computational power and time delays. Use cases show the impact of these limitations on machine health monitoring. Additionally, an automated bearing health monitoring algorithm is developed to show the benefits of both architectures.

SUBJECT:	M.S. Thesis Presentation

BY:	Marcel Neumann

TIME:	Wednesday, July 1, 2020, 9:00 a.m.

PLACE:	https://bluejeans.com/475478772, N/A

TITLE:	Edge-based Machine Monitoring Architectures Incorporating OPC UA Controller Data

COMMITTEE:	Dr. Christopher Saldana, Chair (ME) Dr. Thomas Kurfess (ME) Dr. Cristina Tarín (University of Stuttgart) Dr. Oliver Sawodny (University of Stuttgart)

SUMMARY The usage of external sensors for machine health monitoring is becoming more popular. A variety of methods for monitoring the condition of CNC machines have been developed by researchers. This study focuses on automation principles for these methods connecting an edge device for sensor data acquisition to the OPC UA controller server of a CNC machine. For this purpose, two different architectures are developed and analyzed in experiments to identify the limitations regarding computational power and time delays. Use cases show the impact of these limitations on machine health monitoring. Additionally, an automated bearing health monitoring algorithm is developed to show the benefits of both architectures.