Asset Performance Management with AR
summary
Argues that combining AR, IoT and machine learning creates manipulable asset models like a digital twin of a turbine that fuses speed temperature vibration logs drawings and repair history so analysts can spot failure modes and predict unplanned downtime using real time access to large datasets He demonstrates a simple colorized matrix to expose anomalies and claims analysis that explains why things fail is a more useful superpower than mere visibility and urges shifting focus from HMDs to network awareness and flow
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chapters (8)
- 0:00Introduction
- 1:10Reality
- 2:26Tesseract
- 2:53Network
- 3:33Flow
- 4:52Data Visualization Example
- 5:22Value of AR
- 6:17Conclusion
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